Jan Schlicht has more than ten years of experience developing complex algorithms and distributed systems, working in both mechanical engineering and the software industry. This dual background gives him an unusual perspective: he understands not only how large-scale software systems behave under real-world constraints, but also how domain experts outside of software work with data day to day.

His technical focus lies in distributed systems, decentralized machine learning, and statistical models. With Katulu, he works to reconcile machine learning with data sovereignty, an increasingly important concern for organizations that need to learn from data they cannot or should not centralize. By bringing machine learning to the data instead of moving data to a central location, this approach lets companies in regulated or distributed settings collaborate and build models without giving up control of sensitive information.